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Enabling smart control by optimally managing the State of Charge of district heating networks

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  • Saletti, Costanza
  • Zimmerman, Nathan
  • Morini, Mirko
  • Kyprianidis, Konstantinos
  • Gambarotta, Agostino

Abstract

Digitalization and smart control of district heating networks are emerging as key features to make these systems flexible and optimal. However, since effective and scalable methods for large-scale systems are currently unavailable, the implementation of smart controllers can be challenging and time-consuming. This is addressed herein by proposing a novel approach to include the thermal capacity of the connected buildings in the optimal control of large-scale heating networks. A reduced-order model of the aggregated communities supplied by a large-scale network is used to define their State of Charge, which is exploited to store or retrieve energy when convenient, while maintaining indoor comfort. This concept is included in a Model Predictive Controller that optimizes power plant management and heat distribution. The results show that the controller successfully shaves heat supply peaks to different regions up to 16% and reduces the difference between distribution and soil temperature up to 20%. At the same time, the return temperature is kept close to the set-point of 35 °C, which is lower than the historical operation and further reduces distribution heat losses. The procedure can be easily replicated to optimize systems of different sizes and to support their transition to efficient, smart district heating networks.

Suggested Citation

  • Saletti, Costanza & Zimmerman, Nathan & Morini, Mirko & Kyprianidis, Konstantinos & Gambarotta, Agostino, 2021. "Enabling smart control by optimally managing the State of Charge of district heating networks," Applied Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:appene:v:283:y:2021:i:c:s0306261920316743
    DOI: 10.1016/j.apenergy.2020.116286
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    1. Harney, Patrick & Gartland, Donna & Murphy, Fionnuala, 2020. "Determining the optimum low-temperature district heating network design for a secondary network supplying a low-energy-use apartment block in Ireland," Energy, Elsevier, vol. 192(C).
    2. Leśko, Michał & Bujalski, Wojciech & Futyma, Kamil, 2018. "Operational optimization in district heating systems with the use of thermal energy storage," Energy, Elsevier, vol. 165(PA), pages 902-915.
    3. Le Dréau, J. & Heiselberg, P., 2016. "Energy flexibility of residential buildings using short term heat storage in the thermal mass," Energy, Elsevier, vol. 111(C), pages 991-1002.
    4. Fazlollahi, Samira & Schüler, Nils & Maréchal, François, 2015. "A solid thermal storage model for the optimization of buildings operation strategy," Energy, Elsevier, vol. 88(C), pages 209-222.
    5. Arabkoohsar, Ahmad & Alsagri, Ali Sulaiman, 2020. "A new generation of district heating system with neighborhood-scale heat pumps and advanced pipes, a solution for future renewable-based energy systems," Energy, Elsevier, vol. 193(C).
    6. Arnaudo, Monica & Topel, Monika & Puerto, Pablo & Widl, Edmund & Laumert, Björn, 2019. "Heat demand peak shaving in urban integrated energy systems by demand side management - A techno-economic and environmental approach," Energy, Elsevier, vol. 186(C).
    7. Chambers, Jonathan & Narula, Kapil & Sulzer, Matthias & Patel, Martin K., 2019. "Mapping district heating potential under evolving thermal demand scenarios and technologies: A case study for Switzerland," Energy, Elsevier, vol. 176(C), pages 682-692.
    8. Lund, Henrik & Østergaard, Poul Alberg & Chang, Miguel & Werner, Sven & Svendsen, Svend & Sorknæs, Peter & Thorsen, Jan Eric & Hvelplund, Frede & Mortensen, Bent Ole Gram & Mathiesen, Brian Vad & Boje, 2018. "The status of 4th generation district heating: Research and results," Energy, Elsevier, vol. 164(C), pages 147-159.
    9. Guelpa, Elisa & Marincioni, Ludovica, 2019. "Demand side management in district heating systems by innovative control," Energy, Elsevier, vol. 188(C).
    10. Mazhar, Abdur Rehman & Liu, Shuli & Shukla, Ashish, 2018. "A state of art review on the district heating systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 420-439.
    11. Kouhia, Mikko & Laukkanen, Timo & Holmberg, Henrik & Ahtila, Pekka, 2019. "District heat network as a short-term energy storage," Energy, Elsevier, vol. 177(C), pages 293-303.
    12. Koschwitz, D. & Frisch, J. & van Treeck, C., 2018. "Data-driven heating and cooling load predictions for non-residential buildings based on support vector machine regression and NARX Recurrent Neural Network: A comparative study on district scale," Energy, Elsevier, vol. 165(PA), pages 134-142.
    13. Connolly, D. & Lund, H. & Mathiesen, B.V. & Werner, S. & Möller, B. & Persson, U. & Boermans, T. & Trier, D. & Østergaard, P.A. & Nielsen, S., 2014. "Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system," Energy Policy, Elsevier, vol. 65(C), pages 475-489.
    14. Suryanarayana, Gowri & Lago, Jesus & Geysen, Davy & Aleksiejuk, Piotr & Johansson, Christian, 2018. "Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods," Energy, Elsevier, vol. 157(C), pages 141-149.
    15. Hast, Aira & Syri, Sanna & Lekavičius, Vidas & Galinis, Arvydas, 2018. "District heating in cities as a part of low-carbon energy system," Energy, Elsevier, vol. 152(C), pages 627-639.
    16. Guelpa, Elisa & Marincioni, Ludovica & Deputato, Stefania & Capone, Martina & Amelio, Stefano & Pochettino, Enrico & Verda, Vittorio, 2019. "Demand side management in district heating networks: A real application," Energy, Elsevier, vol. 182(C), pages 433-442.
    17. Guelpa, Elisa & Verda, Vittorio, 2019. "Thermal energy storage in district heating and cooling systems: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    18. Lund, Henrik & Werner, Sven & Wiltshire, Robin & Svendsen, Svend & Thorsen, Jan Eric & Hvelplund, Frede & Mathiesen, Brian Vad, 2014. "4th Generation District Heating (4GDH)," Energy, Elsevier, vol. 68(C), pages 1-11.
    19. De Lorenzi, Andrea & Gambarotta, Agostino & Morini, Mirko & Rossi, Michele & Saletti, Costanza, 2020. "Setup and testing of smart controllers for small-scale district heating networks: An integrated framework," Energy, Elsevier, vol. 205(C).
    20. Dotzauer, Erik, 2002. "Simple model for prediction of loads in district-heating systems," Applied Energy, Elsevier, vol. 73(3-4), pages 277-284, November.
    21. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    22. Li, Xue & Li, Wenming & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Li, Guoqing, 2020. "Collaborative scheduling and flexibility assessment of integrated electricity and district heating systems utilizing thermal inertia of district heating network and aggregated buildings," Applied Energy, Elsevier, vol. 258(C).
    23. Vandermeulen, Annelies & van der Heijde, Bram & Helsen, Lieve, 2018. "Controlling district heating and cooling networks to unlock flexibility: A review," Energy, Elsevier, vol. 151(C), pages 103-115.
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